The invention relates generally to the field of medical imaging. More particularly, the present invention relates to a technique for automatically identifying and labeling blood vessels in a medical image.
Volumetric medical imaging systems have become a valuable tool in the diagnosis and treatment of many illnesses and diseases. As opposed to conventional X-ray imaging systems that are only able to gather only two-dimensional information about a patient's internal anatomical features, volumetric medical imaging systems are able to gather internal anatomical information in three-dimensions. This three-dimensional information can then be used to form medical images from a variety of different perspectives, whereas conventional X-ray images are limited to an image from a single view. Examples of volumetric imaging systems are Computed Tomography (CT) imaging systems, Magnetic Resonance Imaging (MRI) systems, and Positron Emission Tomography (PET).
One factor that can impair the usefulness of these imaging technologies is the relative difficulty in discerning a particular structure of interest from its background, especially when the background has a similar texture or structure. Segmentation programs have been developed to facilitate the examination of specific anatomical features by eliminating non-desired anatomical features from the image. For example, segmentation programs have been developed that enable bone to be removed from an image so that soft tissues may be observed more easily. In some applications, problems in identifying an anatomical feature may still exist after segmentation. For example, a segmentation program may be used to segment the blood vessels within the skull that supply the brain from other soft tissues and bone. However, the large number of blood vessels remaining after segmentation makes identifying a specific blood vessel difficult. In addition, the blood vessels of the brain make many twists and turns, as well as intertwine, making it even more difficult to identify a specific blood vessel. As a result, it may be difficult to identify or track an individual blood vessel as it courses its way around the brain.
Images of the blood vessels of the brain are of great interest to radiologists. For example, a radiologist will be interested in identifying the blood vessel segment that is occluded if the purpose of a scan is for the detection of an ischemic stroke. On the other hand, if the purpose of the scan is the detection of a hemorrhagic stroke, a radiologist will be interested in locating vessel junctions (or bifurcation points), which are a common location of aneurysms. However, a normal segmented image of the blood vessels of the brain may not be particularly helpful in either situation. It may be difficult for the radiologist to identify the specific blood vessel involved. Furthermore, it may be difficult to distinguish a bifurcation point in a blood vessel from simply the overlapping of two blood vessels.
Therefore, a need exists for a technique that will overcome the problems described above. The techniques described below may solve one or more of these problems.